Ontology-based query answering has to be supported w.r.t. secondary memory and very expressive ontologies to meet practical requirements in some applications. Recently, advances for the expressive DL SHI have been made in the dissertation of S. Wandelt for conceptbased instance retrieval on Big Data descriptions stored in secondary memory. In this paper we extend this approach by investigating optimization algorithms for answering grounded conjunctive queries.
